The group fused Lasso for multiple change-point detection
Duration: 46 mins 57 secs
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About this item
| Description: |
Vert, J-P (Mines ParisTech)
Friday 17 January 2014, 09:30-10:15 |
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| Created: | 2014-01-24 12:01 |
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| Collection: | Inference for Change-Point and Related Processes |
| Publisher: | Isaac Newton Institute |
| Copyright: | Vert, J-P |
| Language: | eng (English) |
| Abstract: | We present the group fused Lasso for detection of multiple change-points shared by a set of co-occurring one-dimensional signals. Change-points are detected by approximating the original signals with a constraint on the multidimensional total variation, leading to piecewise-constant approximations. Fast algorithms are proposed to solve the resulting optimization problems, either exactly or approximately. Conditions are given for consistency of both algorithms as the number of signals increases, and empirical evidence is provided to support the results on simulated and array comparative genomic hybridization data. |
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